scholarly journals Clinical usefulness and feasibility of time-frequency analysis of chemosensory event-related potentials

2013 ◽  
Vol 51 (3) ◽  
pp. 210-221
Author(s):  
C. Huart ◽  
Ph Rombaux ◽  
T. Hummel ◽  
A. Mouraux
Keyword(s):  
Frequency Analysis ◽  
Time Domain ◽  
Signal To Noise Ratio ◽  
Discrimination Performance ◽  
Clinical Usefulness ◽  
Olfactory Stimulation ◽  
Signal To Noise ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Time Domain Averaging

Background: The clinical usefulness of olfactory event-related brain potentials (OERPs) to assess olfactory function is limited by the relatively low signal-to-noise ratio of the responses identified using conventional time-domain averaging. Recently, it was shown that time-frequency analysis of the obtained EEG signals can markedly improve the signal-to-noise ratio of OERPs in healthy controls, because it enhances both phase-locked and non phase-locked EEG responses. The aim of the present study was to investigate the clinical usefulness of this approach and evaluate its feasibility in a clinical setting. Methodology: We retrospectively analysed EEG recordings obtained from 45 patients (15 anosmic, 15 hyposmic and 15 normos- mic). The responses to olfactory stimulation were analysed using conventional time-domain analysis and joint time-frequency analysis. The ability of the two methods to discriminate between anosmic, hyposmic and normosmic patients was assessed using a Receiver Operating Characteristic analysis. Results: The discrimination performance of OERPs identified using conventional time-domain averaging was poor. In contrast, the discrimination performance of the EEG response identified in the time-frequency domain was relatively high. Furthermore, we found a significant correlation between the magnitude of this response and the psychophysical olfactory score. Conclusion: Time-frequency analysis of the EEG responses to olfactory stimulation could be used as an effective and reliable diagnostic tool for the objective clinical evaluation of olfactory function in patients.

The Time-Frequency Analysis for Energy Dissipation Shed-Tunnel’s Rockfall Impact Signal Based on Wavelet Theory

2011 ◽  
Vol 243-249 ◽  
pp. 5085-5088
Author(s):  
Lin Feng Wang ◽  
Hong Mei Tang ◽  
Hong Kai Chen
Keyword(s):  
Energy Dissipation ◽  
Frequency Analysis ◽  
Calculation Result ◽  
Signal To Noise Ratio ◽  
Prevention Measures ◽  
Autocorrelation Analysis ◽  
Wavelet Theory ◽  
Signal To Noise ◽  
Time Frequency Analysis ◽  
Time Frequency

Shed-tunnel is one of common prevention measures along the highway. Through the wavelet theory we denoised the rockfall impact signal when the rock impact the ordinary shed-tunnel and the energy dissipation shed-tunnel. And then we evaluated the wavelet theory’s denoise effect by the signal-to-noise ratio. The calculation result indicated that the denoise effect is very good. At last, through the autocorrelation analysis and time-frequency analysis for the rockfall impact signal, it was found that the ordinary shed-tunnel’s impact signals didn’t have obvious frequency and the frequency contained many component,but the energy dissipation shed-tunnel’s impact signals had obvious frequency. So the energy dissipation shed-tunnel’s impact signals had a relatively fixed cycle and frequency. The received frequency of rockfall impact by the time-frequency analysis could provide the basis for the design of energy dissipation shed-tunnel’s natural frequency.

scholarly journals Pre and Post-Stack Imaging of 2D Seismic Data Using Time Migration for Ajeel Oil field, Central of Iraq

2019 ◽  
pp. 2186-2195
Author(s):  
Fadhil Abdulabass Obaid ◽  
Ali M. Al-Rahim
Keyword(s):  
Frequency Analysis ◽  
Seismic Data ◽  
Signal To Noise Ratio ◽  
Oil Field ◽  
Seismic Survey ◽  
Signal To Noise ◽  
Final Time ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Time Migration

Kirchhoff Time migration was applied in Pre and Post-Stack for 2D seismic survey for line AJ-99N, that is located in Ajeel oilfield in Salah Al-Din Governorate, Central Iraq. The process follows several accurate steps to reach the final time migration stage. The results of applied time migration give an accurate image for the Ajeel anticline reservoir and to improve the signal to noise ratio. Pre-Stack shows a clearer image for the structure in the study area, and the time-frequency analysis insure the result.

Time Frequency Domain Analysis of the Dispersion of Guided Wave Modes

2004 ◽  
Author(s):  
Youn-Ho Cho ◽  
Yong-Kwon Kim ◽  
Ik-Keun Park
Keyword(s):  
Wavelet Transform ◽  
Group Velocity ◽  
Frequency Analysis ◽  
Time Domain ◽  
Excitation Frequency ◽  
Guided Wave ◽  
Time Frequency Analysis ◽  
Mode Identification ◽  
Time Frequency ◽  
Wave Modes

One of unique characteristics of guided waves is a dispersive behavior that guided wave velocity changes with an excitation frequency and mode. In practical applications of guided wave techniques, it is very important to identify propagating modes in a time-domain waveform for determination of defect location and size. Mode identification can be done by measurement of group velocity in a time-domain waveform. Thus, it is preferred to generate a single or less dispersive mode. But, in many cases, it is difficult to distinguish a mode clearly in a time-domain waveform because of superposition of multi modes and mode conversion phenomena. Time-frequency analysis is used as efficient methods to identify modes by presenting wave energy distribution in a time-frequency. In this study, experimental guided wave mode identification is carried out in a steel plate using time-frequency analysis methods such as wavelet transform. The results are compared with theoretically calculated group velocity dispersion curves. The results are in good agreement with analytical predictions and show the effectiveness of using the wavelet transform method to identify and measure the amplitudes of individual guided wave modes.

Extracting of Micro Doppler Parameter of Helicopter Rotor Based on Time-Frequency Analysis

2011 ◽  
Vol 130-134 ◽  
pp. 2696-2700 ◽  
Author(s):  
Lei Zhang ◽  
Guo Qing Huang
Keyword(s):  
Frequency Domain ◽  
Frequency Analysis ◽  
Time Domain ◽  
Good Method ◽  
Helicopter Rotor ◽  
Echo Signal ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Radar Echo ◽  
Doppler Parameter

The micro Doppler effect of the radar echo signal of helicopter rotor is studied, and the formula of helicopter rotor echo is obtained. Then the received echo signal of helicopter rotor simulated is analyzed in time domain, frequency domain and time-frequency domain respectively, the analysis results show that it is a good method to extract micro Doppler of helicopter rotor echo by time-frequency analysis. According to analysis results, obtained a method to determine parity of blades and velocity of helicopter rotor, these methods can be used to identify helicopter.

Diagnosis of damaged wind turbine blade by noise characteristics

2020 ◽  
Vol 68 (2) ◽  
pp. 146-156
Author(s):  
Chao-Nan Wang ◽  
Tang-Yao Chi
Keyword(s):  
Feature Extraction ◽  
Wind Turbine ◽  
Turbine Blade ◽  
Frequency Analysis ◽  
Time Domain ◽  
Wind Turbine Blade ◽  
Statistical Regression ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Noise Characteristics

This study has proposed two estimation models of noise signal characteristic diagnosis based on time-domain and time-frequency analysis. The diagnosis of time domain was based on the fractal theory, and the result of fractal dimensions was converted into Gauss distribution, so as to provide a feature extraction for abnormality diagnosis of damaged blade. In addition, for time-frequency analysis, the wavelet methodwas used as the basis of signal analysis. The Morlet transform and mother wavelet were used for wavelet analysis of signal to obtain the result of time-frequency analysis. When the time axis was integrated, the marginal spectrum of frequency domain was obtained, and statistical regression analysis was used to provide another method of feature extraction diagnosis. The wind turbine blade signal was measured in actual wind turbine operation at Changhua Coastal Industrial Park for diagnostic analysis, so as to provide a multi-diagnostic model of wind turbine blade prewarning and health management models.

Simulation in the Time Domain and Time-Frequency Analysis for Coherent Doppler Wind Lidar

2015 ◽  
Vol 42 (1) ◽  
pp. 0114003
Author(s):  
白雪 Bai Xue ◽  
郭磐 Guo Pan ◽  
陈思颖 Chen Siying ◽  
张寅超 Zhang Yinchao ◽  
陈和 Chen He ◽  
...  
Keyword(s):  
Frequency Analysis ◽  
Time Domain ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Wind Lidar ◽  
The Time Domain ◽  
Doppler Wind Lidar

A Novel Imaging Approach for Dispersive Target Electromagnetic Imaging

2013 ◽  
Vol 427-429 ◽  
pp. 1972-1976
Author(s):  
Guo Rong Huang ◽  
Wei Jun Zhong ◽  
Chao Wang ◽  
Yuan Pei Wu
Keyword(s):  
Frequency Analysis ◽  
Time Domain ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Electromagnetic Wave Scattering ◽  
Electromagnetic Imaging ◽  
Imaging Experiment ◽  
Imaging Approach ◽  
The Time Domain ◽  
Difference Time

A novel imaging approach for dispersive target electromagnetic imaging based on the time-frequency analysis is presented in this paper. On the foundation of researching the time-domain imaging principle of dispersive target, the basic theory of back projection imaging algorithm and time-frequency analysis is discussed. The sampling data obtained by simulation of target electromagnetic wave scattering which is accomplished by finite-difference time domain method (FDTD). According to the simulating data, after disposing by Wigner-Ville transfer, the sampling data is processed integral management in frequency-domain, and the imaging experiment is carried out. The experiment results show that the improved imaging arithmetic could estimate the shape of dispersive target and improve the imaging quality.

The Applied Research of Time-Frequency Analysis Method Employed in Seismic Signal Processing

2014 ◽  
Vol 955-959 ◽  
pp. 1809-1812
Author(s):  
Zuo Ju Wu ◽  
Zhi Jia Wang ◽  
Jun Wei Bi
Keyword(s):  
Frequency Domain ◽  
Frequency Analysis ◽  
Time Domain ◽  
Seismic Signal ◽  
Frequency Domain Analysis ◽  
Analysis Method ◽  
Time Frequency Analysis ◽  
Hilbert Huang Transform ◽  
Time Frequency ◽  
Seismic Signal Processing

In the traditional processing of seismic signal, the frequency domain analysis method is always available to research some features which always vary with frequency. However, the condition of parameters which vary with time going can’t be considered in this method. So all the information in time domain have been neglected. In this article, time-frequency analysis method called HHT(Hilbert-Huang transform) is applied to analyze the Qingping wave of Wenchuan earthquake meticulously, which is the most advantaged to dissect the change features of the seismic record at different scales. Then we can get the dual properties in time domain and the frequency domain, such as the IMF function of each modal and the instantaneous frequency. For reflecting the time-frequency characteristics exactly and clearly, the Hilbert spectrum has been used to show these messages in the time-frequency plane.

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